13 Aug Where does time go in a clinical trial — and why does it matter more than most sponsors think
Clinical trials take a long time. This is treated as a structural feature of the field rather than a management problem. Development timelines measured in years have become a baseline assumption for sponsors, CROs, and site staff alike. What gets less attention is how much of that time is consumed by work that is not the trial itself.
The Tufts Center for the Study of Drug Development has tracked protocol complexity over two decades and found consistent increases in endpoints, procedures, and eligibility criteria per trial. Between 2001 and 2020, the average number of endpoints per protocol increased by 86%, and the number of procedures per protocol more than doubled. Each addition creates downstream administrative and operational work that falls on site staff, CRO monitors, and sponsor teams.
The labor implications are substantial. A 2020 analysis published in Therapeutic Innovation and Regulatory Science found that staff time is the largest single cost driver in clinical trial operations, accounting for a majority of site costs in Phase II and Phase III studies. Most organizations have limited visibility into how that time is actually distributed across trial activities — which makes it difficult to identify where it accumulates unnecessarily, and harder to model staffing requirements accurately for future studies.
The Documentation Burden
Regulatory requirements around clinical trial documentation are not optional, and that burden has grown alongside protocol complexity. Site staff managing a multi-site study typically spend significant portions of their time on source document verification, query resolution, and protocol deviation reporting — work that is necessary but whose volume depends heavily on how well the protocol was designed and how clearly procedures were communicated at startup.
The gap between what regulatory documentation requires and what is actually captured varies by site and by trial. Sites with well-defined internal processes for tracking staff activity against specific trial tasks tend to catch discrepancies earlier and resolve them faster. Those without clear time allocation records often find that audits surface gaps between what was documented and what was done, creating remediation work that compounds the original problem.
How CROs Manage the Labor Question
Contract research organizations absorb a large portion of clinical trial operational work. By most estimates, CROs now manage the majority of industry-sponsored trials, and that share has grown as sponsors have shifted toward leaner internal operations. The CRO business model depends on accurate labor estimation: proposals are priced on projected hours, profitability is determined by whether actual hours match those projections, and repeat business reflects whether the sponsor’s experience tracked with expectations.
In practice, labor estimation in clinical research has historically relied on benchmarks and experience rather than data from previous studies. When organizations track staff time against specific trial activities using tools like actiTIME, designed for clinical trials operations, they accumulate actual data on how long regulatory submissions take, how many monitor hours a particular site type requires, and how protocol amendments affect staff time downstream. That data changes estimation from a judgment call to something that can be examined and adjusted.
For CROs, the question of where time goes is also a financial question. A study that runs 15% over its projected hours erodes the contract margin, and the causes of that overrun are often not visible until the study closes. Time tracking configured for CRO workflows gives operations teams a running picture of hours against budget by study, site, and activity type — which allows course correction while the study is still running rather than a post-mortem that can only inform the next proposal.
The Site Staffing Problem
Clinical research coordinators are the primary labor resource at investigative sites. They manage consent, source data collection, protocol adherence, and communication with monitors and sponsors across however many concurrent studies the site is running. Coordinator turnover is consistently cited as one of the main sources of site performance variability in multi-site trials — when a coordinator leaves mid-study, the replacement requires training and the transition creates documentation risk.
Less often discussed is that coordinator workload is usually opaque to site leadership. Hours are tracked at the level of enrollment numbers rather than labor input. A site struggling to maintain documentation quality may be struggling because coordinators are carrying too many concurrent studies, or because a specific protocol is administratively heavier than estimated, or because one sponsor’s query volume is running high. Without time data, the symptom is visible. The cause is not.
The Regulatory Timeline as a Labor Problem
Regulatory submissions have their own time demands, sitting outside the trial execution timeline but drawing from the same staff resources. IND submissions, protocol amendments, and safety reporting require significant coordinator and investigator time that is often absent from operational planning, particularly at sites running multiple studies on overlapping timelines.
The FDA’s ongoing emphasis on data integrity — reinforced through guidance documents and inspection findings over the past decade — has raised the documentation standards sites must meet. Each documentation requirement is a labor requirement. Sites and sponsors that can map regulatory compliance activities onto staff time are better positioned to resource those activities and to anticipate where capacity constraints will emerge as a study moves through its phases.
What Time Visibility Actually Changes
Better operational time tracking in clinical research is not primarily a cost-reduction project, though cost data is a real output. The more direct value is information quality. When organizations cannot see where trial labor is going, decisions about protocol design, site selection, CRO scope, and study budgeting rest on inadequate data. Estimates don’t reflect reality, budgets require amendment, and sites carry load that was not planned for.
Trials that systematically track staff time against activity categories accumulate evidence about what actually drives labor — in a given therapeutic area, for a given protocol type, at a given level of site complexity. That evidence makes future planning more accurate and conversations with sponsors and regulators more defensible, because the organization can show what resources it applied to specific activities rather than providing aggregate figures.
The time a clinical trial takes is partly outside any organization’s control. The regulatory clock, site activation delays, and enrollment variability are real. Where staff time goes within those constraints is more measurable than the field has generally treated it, and that gap is probably worth closing.
For a broader overview of how CROs manage the full operational scope of modern clinical trials — from regulatory compliance to data management and site oversight — see this MedicalResearch.com overview of clinical trials CROs as the backbone of successful clinical research.
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Last Updated on August 13, 2026 by Marie Benz MD FAAD